On the one hand: this is a little bit of evidence that you can get reasoning and a small world model/something that maybe looks like an inner monologue easily out of ‘shallow heuristics’, without anything like general intelligence, pointing towards continuous progress and narrow AIs being much more useful. Plus it’s a scale up and presumably more expensive than predecessor models (used a lot more TPUs), in a field that’s underinvested.
On the other hand, it looks like there’s some things we might describe as ‘emergent capabilities’ showing up, and the paper describes it as discontinous and breakthroughs on certain metrics. So a little bit of evidence for the discontinous model? But does the Eliezer/pessimist model care about performance metrics like BIG-bench tasks or just qualitative capabilities (i.e. the ‘breakthrough capabilities’ matter but discontinuity on performance metrics don’t)?
So, how does this do as evidence for Paul’s model over Eliezer’s, or vice versa? As ever, it’s a tangled mess and I don’t have a clear conclusion.
https://astralcodexten.substack.com/p/yudkowsky-contra-christiano-on-ai
On the one hand: this is a little bit of evidence that you can get reasoning and a small world model/something that maybe looks like an inner monologue easily out of ‘shallow heuristics’, without anything like general intelligence, pointing towards continuous progress and narrow AIs being much more useful. Plus it’s a scale up and presumably more expensive than predecessor models (used a lot more TPUs), in a field that’s underinvested.
On the other hand, it looks like there’s some things we might describe as ‘emergent capabilities’ showing up, and the paper describes it as discontinous and breakthroughs on certain metrics. So a little bit of evidence for the discontinous model? But does the Eliezer/pessimist model care about performance metrics like BIG-bench tasks or just qualitative capabilities (i.e. the ‘breakthrough capabilities’ matter but discontinuity on performance metrics don’t)?